Dirichlet Process Priors for Small Area Estimation and Disease Mapping


Session:

Ranking, Sparseness and Clustering in Disease Mapping

Authors:
Malay Ghosh (Department of Statistics, University of Florida) (Speaker)
Xueying Tang (Department of Statistics, University of Florida)
Abstract:

We illustrate some applications of Dirichlet Process Priors for modeling random effects in small area models. We also show some of its application in disease mapping by using a Dirichlet process prior with a baseline CAR model. One advantage of such priors is that there is automatic clustering as well as tracking a multimodal posterior much more accurately than normal random effects model.